Bioscience trends最新文献

Hepatocellular carcinoma (HCC) is the fourth leading cause of cancer death worldwide and its prognosis is highly heterogeneous, being related not only to underlying chronic liver disease but also to the severity of cancer cachexia. Nutritional factors play a crucial role in influencing the prognosis of HCC. Despite musculoskeletal imbalance being consistently reported as a predictor of perioperative mortality in patients with HCC, this condition is often overlooked in clinical management. Bone mineral density (BMD), which serves as a marker of nutritional status, can be assessed through CT by measuring the pixel density of the vertebral bone. Recent clinical studies have indicated that BMD serves not only as a significant risk factor for development of HCC in cirrhotic patients but also potentially functions as an independent prognostic indicator for post-treatment outcomes in patients with HCC. Preoperative abdominal CT scans provide a convenient and cost-effective method to measure BMD, offering significant assistance in prognostic evaluation of patients with HCC. A thorough grasp of the liver-bone connection, along with the conduct of higher-quality studies and the establishment of standardized methods and cutoff values for BMD measurement, could enhance approaches to manage HCC.

To establish clinical prediction models of vessels encapsulating tumor clusters (VETC) pattern using preoperative contrast-enhanced ultrasound (CEUS) and gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid magnetic resonance imaging (EOB-MRI) in patients with hepatocellular carcinoma (HCC). A total of 111 resected HCC lesions from 101 patients were included. Preoperative imaging features of CEUS and EOB-MRI, postoperative recurrence, and survival information were collected from medical records. The best subset regression and multivariable Cox regression were used to select variables to establish the prediction model. The VETC-positive group had a statistically lower survival rate than the VETC-negative group. The selected variables were peritumoral enhancement in the arterial phase (AP), hepatobiliary phase (HBP) on EOB-MRI, intratumoral branching enhancement in the AP of CEUS, intratumoral hypoenhancement in the portal phase of CEUS, incomplete capsule, and tumor size. A nomogram was developed. High and low nomogram scores with a cutoff value of 168 points showed different recurrence-free survival rates and overall survival rates. The area under the curve (AUC) and accuracy were 0.804 and 0.820, respectively, indicating good discrimination. Decision curve analysis showed a good clinical net benefit (threshold probability > 5%), while the Hosmer-Lemeshow test yielded excellent calibration (P = 0.6759). The AUC of the nomogram model combining EOB-MRI and CEUS was higher than that of the models with EOB-MRI factors only (0.767) and CEUS factors only (0.7). The nomogram verified by bootstrapping showed AUC and calibration curves similar to those of the nomogram model. The Prediction model based on CEUS and EOB-MRI is effective for preoperative noninvasive diagnosis of VETC.

Aging is a challenge to global development. This challenge is particularly significant for China because it has the largest elderly population worldwide. The proportion of aging population continues to increase, and solely relying on government efforts to meet the needs of the elderly is inadequate. Hence, involvement of social organizations in elderly care services is needed. Their core members exhibit higher sense of responsibility and identification with the organization than regular members, thus profoundly affecting organizational development. Based on the Social Capital Theory, this study employed a multistage stratified random sampling method to examine the social capital stock of elderly social organizations and their core members across six cities in Anhui Province, China. Chi-square tests analyzed the relationship between the core members' demographic factors and individual performance. Independent-sample t-tests assessed the relationship between social capital and individual performance. Finally, binary logistic regression models determined the factors influencing the individual performance of core members. Social networks within core members' social capital and the internal social capital of elderly caring social organizations (ESOs) affect the individual performance of core members. Therefore, organizations should provide more training opportunities for core members to expand their networks. Cultivating a shared language and vision as components of social capital can enhance organizational cohesion and operational stability.

Population aging is a global concern, and Japan currently has the world's highest proportion of an aging population. In 2020, the population age 65 and over accounted for 10% of the global population, while this proportion was 29% in Japan, and it is expected to reach 38.4% in 2065. The average life expectancy in Japan in 2022 was 81.05 for males and 87.09 for females. At the same time, Japan's healthy life expectancy continues to increase, and it is increasing at a faster rate than the average life expectancy, with males expected to live 72.68 years and females expected to live 75.38 years in 2019. This is causing the social role of elderly people in Japan to constantly change. The Japanese Government continues to adjust its policy orientation, to improve the health level and social participation of the elderly, improve the accessibility of long-term nursing services and the treatment of nursing professionals, and improve the pension system. By 2025, one-fifth of people in Japan are expected to suffer from dementia. Japan has implemented a series of policies to create a dementia-inclusive and less risky society. The proportion of the population ages 65 and over living alone in Japan increased from 4.3% among males and from 11.2% among females in 1980 to 15.0% among males and 22.1% among females in 2020, representing a sustained increase. Changes in the composition of the population have prompted sustained attention to the personalization and diversification of elderly care. At the same time, Japanese researchers continue to utilize scientific and information technology to innovate elderly care products, improve the efficiency of elderly care, and provide intelligent elderly care.

In recent years, the market for wearable devices has been rapidly growing, with much of the demand for health management. These devices are equipped with numerous sensors that detect inertial measurements, electrocardiograms, photoplethysmography signals, and more. Utilizing the collected data enables the monitoring and analysis of the user's health status in real time. With the proliferation of wearable devices, research on applications such as human activity recognition, anomaly detection, and disease prediction has advanced by combining these devices with deep learning technology. Analyzing heart rate variability and activity data, for example, enables the early detection of an abnormal health status and prompt, appropriate medical interventions. Much of the current research focuses on short-term predictions, but adopting a long-term perspective is essential for further development of wearable devices and deep learning. Continuously recording user behavior, anomalies, and physical information and collecting and analyzing data over an extended period will enable more accurate disease predictions and lifestyle guidance based on individual habits and physical conditions. Achieving this requires the integration of wearable devices with medical records. A system needs to be created to integrate data collected by wearable devices with medical records such as electronic health records in collaboration with medical facilities like hospitals and clinics. Overcoming this challenge will enable optimal health management and disease prediction for each user, leading to a higher quality of life.

This study aims to determine the predictive role of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) derived radiomic model in tumor immune profiling and immunotherapy for cholangiocarcinoma. To perform radiomic analysis, immune related subgroup clustering was first performed by single sample gene set enrichment analysis (ssGSEA). Second, a total of 806 radiomic features for each phase of DCE-MRI were extracted by utilizing the Python package Pyradiomics. Then, a predictive radiomic signature model was constructed after a three-step features reduction and selection, and receiver operating characteristic (ROC) curve was employed to evaluate the performance of this model. In the end, an independent testing cohort involving cholangiocarcinoma patients with anti-PD-1 Sintilimab treatment after surgery was used to verify the potential application of the established radiomic model in immunotherapy for cholangiocarcinoma. Two distinct immune related subgroups were classified using ssGSEA based on transcriptome sequencing. For radiomic analysis, a total of 10 predictive radiomic features were finally identified to establish a radiomic signature model for immune landscape classification. Regarding to the predictive performance, the mean AUC of ROC curves was 0.80 in the training/validation cohort. For the independent testing cohort, the individual predictive probability by radiomic model and the corresponding immune score derived from ssGSEA was significantly correlated. In conclusion, radiomic signature model based on DCE-MRI was capable of predicting the immune landscape of chalangiocarcinoma. Consequently, a potentially clinical application of this developed radiomic model to guide immunotherapy for cholangiocarcinoma was suggested.

Liver transplantation (LT) has been an established treatment for end-staged liver disease for acute, chronic, metabolic diseases and liver cancer. Advanced surgical techniques, refined indications and contraindications for LT, improvements of donor selection, prognostic scorings system and immunosuppressive regimens have contributed to the improved outcomes of liver transplantation. The etiologies of cirrhosis have been shifting from viral hepatitis to metabolic associated fatty liver disease. New indications include peripheral or mass forming bile duct cancer, metastases from bowel cancers or neuroendocrine tumors. Resection and partial liver segments 2-3 transplantation with delayed total hepatectomy has been performed to the limited cases, which was the explored technique of auxiliary partial orthotopic LT. Minimally invasive donor hepatectomy (laparoscopic or robotic) has been increasingly done. In this review are described the recent pressing topics in LT.

The brain-gut axis intricately links gut microbiota (GM) dysbiosis to the development or worsening of autism spectrum disorder (ASD). However, the precise GM composition in ASD and the effectiveness of probiotics are unclear. To address this, we performed a thorough meta-analysis of 28 studies spanning PubMed, PsycINFO, Web of Science, Scopus, and MEDLINE, involving 1,256 children with ASD and 1042 neurotypical children, up to February 2024. Using Revman 5.3, we analyzed the relative abundance of 8 phyla and 64 genera. While individuals with ASD did not exhibit significant differences in included phyla, they exhibited elevated levels of Parabacteroides, Anaerostipes, Faecalibacterium, Clostridium, Dorea, Phascolarctobacterium, Lachnoclostridium, Catenibacterium, and Collinsella along with reduced percentages of Barnesiella, Odoribacter, Paraprevotella, Blautia, Turicibacter, Lachnospira, Pseudomonas, Parasutterella, Haemophilus, and Bifidobacterium. Notably, discrepancies in Faecalibacterium, Clostridium, Dorea, Phascolarctobacterium, Catenibacterium, Odoribacter, and Bifidobacterium persisted even upon systematic exclusion of individual studies. Consequently, the GM of individuals with ASD demonstrates an imbalance, with potential increases or decreases in both beneficial and harmful bacteria. Therefore, personalized probiotic interventions tailored to ASD specifics are imperative, rather than a one-size-fits-all approach.

STK39 is reportedly a critical negative regulator of intestinal barrier. Pharmacological targeting of STK39 is expected to protect the intestinal barrier and thereby weaken metabolic dysfunction-associated steatohepatitis (MASH); Proximal colon biopsy tissues from patients with metabolic dysfunction-associated steatotic liver disease (MASLD) and those without MASLD were analyzed for STK39 expression. Wildtype (WT) mice and systemic STK39 gene knockout (STK39^-/-) male mice were fed a normal diet or a high-fat methionine-choline deficient diet (HFMCD) for 8 weeks. The MASH mice were grouped and treated with ZT-1a (a STK39 inhibitor) or vehicle intraperitoneal injection during the procedure of HFMCD induction. Liver and intestinal tissues were collected for further examination; Colon tissues from patients with MASLD exhibited higher levels of STK39 than those from subjects without MASLD. Knockout of STK39 diminished CD68⁺ Kupffer cells and α-SMA⁺ hepatic stellate cells infiltration in mouse MASH model. Treatment with ZT-1a also prevented severe steatohepatitis in a mouse MASH model, including milder histological and pathological manifestations (lobular inflammation and fibrosis) in the liver. Interestingly, Inhibition of STK39 had minimal effects on hepatic lipid metabolism. The reduced liver injury observed in mice with STK39 inhibition was linked to significant decreases in mucosal inflammation, tight junction disruption and intestinal epithelial permeability to bacterial endotoxins; Collectively, we have revealed that inhibiting STK39 prevents the progression of MASH by protecting the intestinal epithelial barrier.

This study aimed to compare the efficacy and effect on lipid profiles of Ainuovirine (ANV)- and efavirenz (EFV) -based regimens in treatment-naïve people living with HIV-1 (PLWH) at week 24. The proportion of PLWH achieving HIV-1 RNA < the limit of quantification in the ANV group was significantly higher than that in the EFV group (89.18% vs. 76.04%, P = 0.002). The mean change of log₁₀ HIV-1 RNA from baseline was greater (-4.34 vs. -4.18, P < 0.001), the median change from baseline in CD4+ T cell count increased more (106.00 cells/μL vs. 92.00 cells/μL, P = 0.007) in the ANV group, while the CD4+/CD8+ ratio was similar (0.15 vs. 0.20, P = 0.167) between the two groups. The mean changes from baseline in total cholesterol (-0.02 for ANV vs. 0.25 mmol/L for EFV, P < 0.001), triglyceride (-0.14 for ANV vs. 0.11 mmol/L for EFV, P = 0.024), and low-density lipoprotein cholesterol (-0.07 for ANV vs. 0.15 mmol/L for EFV, P < 0.001) was significantly different between the two groups. The percentage of patients with improved lipid profiles was significantly higher in the ANV group (37.44 %) than in the EFV group (29.55%, P = 0.0495). The incidence of any adverse events in the ANV group was significantly lower than that in the EFV group at week 12 (6.2% vs. 30.7%, P < 0.001) and was comparable at week 24 (3.6% vs. 5.5%, P = 0.28). The ANV-based regimen was well tolerated and lipid-friendly in treatment-naïve PLWH.